Although not strictly for forensic purposes, '''visualization tools''' such as the ones discussed here can be very useful for visualizing large data sets. As forensic practitioners need to process more and more data, it is likely that some of the techniques implemented by these tools will need to be adopted.

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This is the list of Training Providers, who offer training courses of interest to practitioners and researchers in the field of Digital Forensics. Conferences which may include training are located on the [[Upcoming_events]] page.

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=Open Source Visualization Toolkits=

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<b>PLEASE READ BEFORE YOU EDIT THE LIST BELOW</b><br>

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Some training providers offer on-going training courses that are available in an on-line "any time" format. Others have regularly scheduled training that is the same time each month. Others have recurring training but are scheduled at various times throughout the year. Providers training courses should be listed in alphabetical order, and should be listed in the appropriate section. Non-Commercial training is typically offered by governmental agencies or organizations that directly support law enforcement. Tool Vendor training is training offered directly by a specific tool vendor, which may apply broadly, but generally is oriented to the vendor's specific tool (or tool suite). Commercial Training is training offered by commercial companies which may or may not be oriented to a specific tool/tool suite, but is offered by a company other than a tool vendor.

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; [http://public.kitware.com/VTK/ The Visualization Toolkit]

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<i>Some training opportunities may be <u>limited</u> to <b>Law Enforcement Only</b> or to a specific audience. Such restrictions should be noted when known.</i>

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: C++ multi-platform with interfaces available for Tcl/Tk, Java and Python. Professional support provided by [http://www.kitware.com/ Kitware].

: Originally developed by the [http://public.research.att.com/areas/visualization/ AT&T Information Visualization Gorup], designed for drawing connected graphs of nodes and edges. Neato is a similar system but does layout based on a spring model. Can produce output as [[PostScript]], [[PNG]], [[GIF]], or as an annotated graph file with the locations of all of the objects---ideal for drawing in a GUI. Runs from the command line on [[Unix]], [[Windows]] and [[Mac]], although there is also a [http://www.pixelglow.com/graphviz/ MacOS GUI version].

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{| border="0" cellpadding="2" cellspacing="2" align="top"

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|- style="background:#bfbfbf; font-weight: bold"

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! width="40%"|Title

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! width="40%"|Website

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! width="20%"|Limitation

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|-

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|Defense Cyber Investigations Training Academy (DCITA)

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|http://www.dc3.mil/dcita/dcitaAbout.php

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|Limited To Certain Roles within US Government Agencies[http://www.dc3.mil/dcita/dcitaRegistration.php (1)]

Revision as of 18:25, 13 June 2014

This is the list of Training Providers, who offer training courses of interest to practitioners and researchers in the field of Digital Forensics. Conferences which may include training are located on the Upcoming_events page.

PLEASE READ BEFORE YOU EDIT THE LIST BELOW
Some training providers offer on-going training courses that are available in an on-line "any time" format. Others have regularly scheduled training that is the same time each month. Others have recurring training but are scheduled at various times throughout the year. Providers training courses should be listed in alphabetical order, and should be listed in the appropriate section. Non-Commercial training is typically offered by governmental agencies or organizations that directly support law enforcement. Tool Vendor training is training offered directly by a specific tool vendor, which may apply broadly, but generally is oriented to the vendor's specific tool (or tool suite). Commercial Training is training offered by commercial companies which may or may not be oriented to a specific tool/tool suite, but is offered by a company other than a tool vendor.

Some training opportunities may be limited to Law Enforcement Only or to a specific audience. Such restrictions should be noted when known.